The present invention relates generally to control systems for power generation and industrial gas turbines. In particular, the invention relates to a gas turbine control system having a Kalman filter applied to tune an electronic model of an industrial gas turbine.
Industrial and power generation gas turbines have control systems (“controllers”) that monitor and control their operation. These controllers govern the combustion system of the gas turbine and other operational aspects of the gas turbine. Typically, the controller executes scheduling algorithms that adjust the fuel flow, inlet guide vanes (IGV) and other control inputs to ensure safe and efficient operation of the gas turbine.
Gas turbine controllers typically receive input values of measured operating parameters and desired operating settings that in conjunction with scheduling algorithms determine settings for control parameters to achieve the desired operation. Measured operating parameters may include but are not limited to compressor inlet pressure and temperature, compressor exit pressure and temperature, turbine exhaust temperature, generator power output. Desired operating settings may include but are not limited to generator power output, and exhaust energy. Control parameters may include but are not limited to fuel flow, combustor fuel splits, compressor inlet guide vane, and inlet bleed heat flow.
It is presumed that the values prescribed by the scheduling algorithms for the control parameters will cause the gas turbine to operate at a desired state, such as at a desired power output level and within defined emission limits. The scheduling algorithms incorporate assumptions regarding the gas turbine, such as that it is operating at a certain efficiency, with a certain flow capacity and at other assumed conditions.
As the gas turbine operates for an extended period, component efficiencies tend to degrade, flow capacities and other operating conditions vary from the assumed conditions. Because of this deterioration, the control scheduling algorithms becomes increasingly out of tune and causes the gas turbine to operate at states that increasingly diverge from the desired operational state.
The feedback signals assist in adjusting the algorithms to compensate for changes in the gas turbine. However, feedback signals do not tune the control scheduling algorithms to entirely compensate for degradation of the performance of the turbine. As performance degrades, the controller has increasing difficulty in operating the gas turbine at the desired operational state.
To correct for changes in the efficiency and flow capacity, the gas turbine is periodically “tuned” which generally requires an engineer or technician to manually adjusts the gas turbine. The gas turbine may needed to be taken off-line to be instrumented for tuning.
There is a long felt need for gas turbine control systems that automatically adjust to changes in the gas turbine, e.g., component efficiencies and flow capacities, that occur during long term operation of the turbine. Further, there is a long felt need for control systems that require less manual tuning than is required for traditional control systems.